• Smart Structures and Systems
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• v.30 no.6
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• pp.673-686
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• 2022

Deep learning algorithms for Structural Health Monitoring (SHM) have been extracting the interest of researchers and engineers. These algorithms commonly used loss functions and evaluation indices like the mean square error (MSE) which were not originally designed for SHM problems. An updated loss function which was specifically constructed for deep-learning-based structural damage detection problems has been proposed in this study. By tuning the coefficients of the loss function, the weights for damage localization and quantification can be adapted to the real situation and the deep learning network can avoid unnecessary iterations on damage localization and focus on the damage severity identification. To prove efficiency of the proposed method, structural damage detection using convolutional neural networks (CNNs) was conducted on a truss bridge model. Results showed that the validation curve with the updated loss function converged faster than the traditional MSE. Data augmentation was conducted to improve the anti-noise ability of the proposed method. For reducing the training time, the normalized modal strain energy change (NMSEC) was extracted, and the principal component analysis (PCA) was adopted for dimension reduction. The results showed that the training time was reduced by 90% and the damage identification accuracy could also have a slight increase. Furthermore, the effect of different modes and elements on the training dataset was also analyzed. The proposed method could greatly improve the performance for structural damage detection on both the training time and detection accuracy.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.271-279
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• 2020

Squats and lunges are important exercises for strengthening the trunk and lower body among various free weight exercises. It should be achieved safe and effective excise through establishing of theoretical basis for exercise posture and standard movement. Therefore, it's necessary to develop the exercise model in order to prepare the scientific countermeasures for the prevent injuries and error movement through optimal exercise movement. For this purpose, it is effective to use appropriate instruments for motion compensation according to the optical motion and error motion. In this paper, we develop a motion model analysis system based on dynamic motion through the four-point load cell for dynamic motion analysis. Proposed analytical method, the optimal and the error motion numerical data is obtained through the dynamic motion analysis. And we verified that dynamic movement is simplified to establish the motion modeling according to the classification motion and the numerical quantification data for analyzing.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.87-96
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• 2020

The purpose of this paper is to develop a fire HRA (Human Reliability Analysis) procedure for full power operation of domestic NPPs (Nuclear Power Plants). For the development of fire HRA procedure, the recent research results of NUREG-1921 in an effort to meet the requirements of the ASME/ANS PRA Standard were reviewed. The K-HRA method, a standard method for HRA of a domestic level 1 PSA (Probabilistic Safety Assessment) and fire related procedures in domestic NPPs were reviewed. Based on the review, a procedure for the fire HRA required for a domestic fire PSA based on the K-HRA method was developed. To this end, HRA issues such as new operator actions required in the event of a fire and complexity of fire situations were considered. Based on the four kinds of HFE (Human Failure Event) developed for a fire HRA in this research, a qualitative analysis such as feasibility evaluation was suggested. And also a quantitative analysis process which consists of screening analysis and detailed analysis was proposed. For the qualitative analysis, a screening analysis by NUREG-1921 was used. In this research, the screening criteria for the screening analysis was modified to reduce vague description and to reflect recent experimental results. For a detailed analysis, the K-HRA method and scoping analysis by NUREG-1921 were adopted. To apply K-HRA to fire HRA for quantification, efforts to modify PSFs (Performance Shaping Factors) of K-HRA to reflect fire situation and effects were made. For example, an absence of STA (Shift Technical Advisor) to command a fire brigade at a fire area is considered and the absence time should be reflected for a HEP (Human Error Probability) quantification. Based on the fire HRA procedure developed in this paper, a case study for HEP quantification such as a screening analysis and detailed analysis with the modified K-HRA was performed. It is expected that the HRA procedure suggested in this paper will be utilized for fire PSA for domestic NPPs as it is the first attempt to establish an HRA process considering fire effects.

• Economic and Environmental Geology
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• v.46 no.1
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• pp.1-9
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• 2013

We proposed the revised full-pattern-fitting method of illite polytype quantification with background correction and scale factor correction of WILDFIRE(C) simulated pattern, and R% value ((${\sum}$|simulated-measured|/simulated)/ $n{\times}100$) calculation, and then verified the reliability of this method by applying for the test sample ($2M_1$:1M$$\frac{._-}{.}$$1:1), and by comparing the result with Grathoff and Moore method (1996). We confirmed that the proposed method showed the error range of less than 3.6%, which is much lower than the previous full-pattern-fitting methods, in spite of the impurities of the test sample. In the comparison with Grathoff and Moore method for 2 tested samples, we obtained the relatively higher $2M_1$ contents using Grathoff and Moore method, whereas we obtained the reliable results with less than 10% of R% values.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.2
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• pp.65-71
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• 2008

A monsoon season monitoring data from June to September, 2005 of a small forested watershed located at the upstream of the North Han River system in Korea was conducted to analyze the flow variations, the NPS pollutant concentrations, and the pollution load characteristics with respect to sampling frequencies. During the 4-month period, 1,423 mm or 79.2% of annual rainfall(1,797 mm) were occurred and more than 77%, 54% and 68% of annual T-N, $NO_3$-N and T-P loads discharged. Flow rate was continuously measured with automatic velocity and water level meters and 58 water quality samples were taken and analyzed. It was analyzed that the flow volume by random measurement varied very widely and ranged from 79% to 218% of that of continuous measurement. It was recommended that flow measurement of small forested watersheds should be continuously measured with automated flow meters to precisely measure flow rates. Flow-weighted mean concentrations of T-N, $NO_3$-N and T-P during the period were 2.114 mg/L, 0.836 mg/L, and 0.136 mg/L, respectively. T-N, $NO_3$-N and T-P loads were sensitive to the number of samples. And it was analyzed that in order to measure the pollution load within the error of 10% to the true load, the rate of sampling frequency should be higher than 89.7% of the sample numbers that were required to compute the true pollution load. If it is compared to selected foreign research results, about 10 water samples for each rainfall event were needed to compute the pollution load within 10% error. It is unlikely in Korea and recommended that thorough NPS pollution monitoring studies are required to develop the standard monitoring procedures for reliable NPS pollution quantification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10B
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• pp.831-840
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• 2004

Providing quality of service (QoS) guarantees over wireless link requires thorough understanding and quantification of the interactions among the traffic source, the wireless channel, and the underlying error control mechanisms. In this paper, we account for such interactions in a network-layer model that we use to investigate the delay performance of a wireless channel. We consider a single ON/OFF traffic stream transported over a wireless link. The capacity of this link fluctuates according to a fluid version of Gilbert-Elliot's model. We derive the packet delay distribution via two different approaches: uniformization and Laplace transform. Numerical aspects of both approaches are compared. The delay distribution is further used to quantify the wireless effective bandwidth under a given delay guarantee. Numerical results and simulations are used to verify the adequacy of our analysis and to study the impact of error control and bandwidth allocation on the packet delay performance. Wireless networks, QoS, delay distribution, fluid analysis.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4114-4114
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• 2001

For the quality control of tablets several parameters have to be checked. The most important one is the content of an active ingredient which has to match a narrow range around the designated content. The only useful measurement mode is transmission which provides information of the complete tablet. A measurement in diffuse reflectance would register only the surface which is useless especially in case of a coated tablet. In this work tablets for a clinical study (placebo/verum studies) with very low concentrations of the active ingredient were measured. The concentration range was 0 to 6 mg with a total weight of the tablets of 105 mg, leading to a highest concentration of the active component of 5.7% by weight. Especially the spectroscopic distinction between the placebo and the low dosage forms with 0.25 and 0.5 mg active agent requires an extraordinarily accurate sampling technique. Using the VECTOR 22/N-T in transmission mode allows the collection of the information from the complete tablets. A quantitative PLS-model with transmission spectra from the tablets described above shows that the active substance can be predicted with a RMSECV (root mean square error of cross validation) of 0.04% absolute for this special application. The results are compared with those of measurements in diffuse reflectance using different accessories.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.187-195
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• 2015

Human-induced initiating events, also called Category B actions in human reliability analysis, are operator actions that may lead directly to initiating events. Most conventional probabilistic safety analyses typically assume that the frequency of initiating events also includes the probability of human-induced initiating events. However, some regulatory documents require Category B actions to be specifically analyzed and quantified in probabilistic safety analysis. An explicit modeling of Category B actions could also potentially lead to important insights into human performance in terms of safety. However, there is no standard procedure to identify Category B actions. This paper describes a systematic procedure to identify Category B actions for low power and shutdown conditions. The procedure includes several steps to determine operator actions that may lead to initiating events in the low power and shutdown stages. These steps are the selection of initiating events, the selection of systems or components, the screening of unlikely operating actions, and the quantification of initiating events. The procedure also provides the detailed instruction for each step, such as operator's action, information required, screening rules, and the outputs. Finally, the applicability of the suggested approach is also investigated by application to a plant example.